1. Field
Embodiments of the present invention generally relate to a system and method for providing customer service and particularly to a system and method for selecting an agent during call routing.
2. Related Art
Contact centers are employed by many enterprises to service inbound and outbound contacts from customers. A typical contact center includes a switch and/or server to receive and route incoming packet-switched and/or circuit-switched contacts and one or more resources, such as human agents and automated resources (e.g., Interactive Voice Response (IVR) units), to service the incoming contacts. Contact centers distribute contacts, whether inbound or outbound, for servicing to any suitable resource according to predefined criteria. In many existing systems, the criteria for servicing the contact from the moment that the contact center becomes aware of the contact until the contact is connected to an agent are client or operator-specifiable (i.e., programmable by the operator of the contact center), via a capability called vectoring. Normally in present-day ACDs when the ACD system's controller detects that an agent has become available to handle a contact, the controller identifies all predefined contact-handling queues for the agent (usually in some order of priority) and delivers to the agent the highest-priority, oldest contact that matches the agent's highest-priority queue. Generally, the only condition that results in a contact not being delivered to an available agent is that there are no contacts waiting to be handled.
The primary objective of contact center management is to ultimately maximize contact center performance and profitability. An ongoing challenge in contact center administration is monitoring and optimizing contact center efficiency. Contact center efficiency is generally measured in two ways.
Service level is one measurement of contact center efficiency. Service level is typically determined by dividing the number of contacts accepted within the specified period by the number accepted plus the number that were not accepted, but completed in some other way (e.g., abandoned, given busy, cancelled, flowed out). Of course, service level definitions may vary from one enterprise to another.
Match rate is another indicator used in measuring contact center efficiency. Match rate is usually determined by dividing the number of contacts accepted by a primary skill level agent within a period of time by the number of contacts accepted by any agent for a queue over the same period. An agent with a primary skill level is one that typically can handle contacts of a certain nature most effectively and/or efficiently. There are other contact center agents that may not be as proficient as the primary skill level agent, and those agents are identified either as secondary skill level agents or backup skill level agents. As can be appreciated, contacts received by a primary skill level agent are typically handled more quickly and accurately or effectively (e.g., higher revenue attained) than a contact received by a secondary or even backup skill level agent. Thus, it is an objective of most contact centers to optimize match rate along with service level.
Traditional contact center technology matches incoming calls to agents based on a combination of knowledge about the customer (business-internal CRM data plus dynamic data retrieved at the beginning of the call), the customer's request, agent availability, agent skill sets, and other factors during the call routing process. Agent scripting software uses the same knowledge about customers and customer service requests as the call routing software.
Traditional call routing and agent scripting rely on sparse, if any, information about callers and coarse-grained customer service requests as well as agent skill sets during the call routing process and agent scripting. Caller information is based on business CRM records and additional caller self-disclosure at the beginning of the call. Customer service requests are mostly as detailed as a short IVR menu or pull-down menu in a web form allows. Such information provides only a small window into callers' preferences, personalities, interests, preferences, handicaps, cultural backgrounds, and into the actual reason for the call. Likewise, agent skill sets are very coarse-grained, highly static, and largely reflect only few dimensions of the agents' true skills, expertise, limitations, and personalities, and are predicated on equally coarse-grained customer service requests (account information, products and services, mailing address, get help etc.).
However, traditional call routing technology does not allow for fine-grained skill set definitions, and assessing agents' detailed skill sets would be a highly time-consuming, costly, and tedious process. The traditional call routing technologies fall short of fine-grained matching of calls (and callers) with agents. Further, there is large impedance between availability of fine-grained customer profiles, even if available, and customer service requests on the one hand and coarse-grained agent skill sets on the other hand.
There is thus a need for an improved customer support service system and method for selecting suitable agents for improved call routing.